Added parallelization to polymer.PersistenceLength

package/CHANGELOG

@@ -16,7 +16,7 @@ The rules for this file:
 -------------------------------------------------------------------------------
 ??/??/?? IAlibay, orbeckst, BHM-Bob, TRY-ER, Abdulrahman-PROG, pbuslaev,
          yuxuanzhuang, yuyuan871111, tanishy7777, tulga-rdn, Gareth-elliott,
-         hmacdope, tylerjereddy, cbouy, talagayev
+         hmacdope, tylerjereddy, cbouy, talagayev, DrDomenicoMarson
 
 
  * 2.10.0
@@ -63,6 +63,8 @@ Enhancements
    (PR #5038)
  * Moved distopia checking function to common import location in
    MDAnalysisTest.util (PR #5038)
+ * Enables parallelization for `analysis.polymer.PersistenceLength` (Issue #4671, PR #5074)
+
 
 Changes
  * Refactored the RDKit converter code to move the inferring code in a separate

package/MDAnalysis/analysis/polymer.py

@@ -40,7 +40,7 @@
 from .. import NoDataError
 from ..core.groups import requires, AtomGroup
 from ..lib.distances import calc_bonds
-from .base import AnalysisBase
+from .base import AnalysisBase, ResultsGroup
 
 logger = logging.getLogger(__name__)
 
@@ -236,8 +236,17 @@ class PersistenceLength(AnalysisBase):
        Former ``results`` are now stored as ``results.bond_autocorrelation``.
        :attr:`lb`, :attr:`lp`, :attr:`fit` are now stored in a
        :class:`MDAnalysis.analysis.base.Results` instance.
+    .. versionchanged:: 2.10.0
+       introduced :meth:`get_supported_backends` allowing for parallel
+       execution on ``multiprocessing`` and ``dask`` backends.
     """
 
+    _analysis_algorithm_is_parallelizable = True
+
+    @classmethod
+    def get_supported_backends(cls):
+        return ("serial", "multiprocessing", "dask")
+
     def __init__(self, atomgroups, **kwargs):
         super(PersistenceLength, self).__init__(
             atomgroups[0].universe.trajectory, **kwargs
@@ -249,15 +258,18 @@ def __init__(self, atomgroups, **kwargs):
         chainlength = len(atomgroups[0])
         if not all(l == chainlength for l in lens):
             raise ValueError("Not all AtomGroups were the same size")
+        self.chainlength = chainlength
 
-        self._results = np.zeros(chainlength - 1, dtype=np.float32)
+    def _prepare(self):
+        self.results.raw_bond_autocorr = np.zeros(
+            self.chainlength - 1, dtype=np.float32
+        )
 
     def _single_frame(self):
         # could optimise this by writing a "self dot array"
         # we're only using the upper triangle of np.inner
         # function would accept a bunch of coordinates and spit out the
         # decorrel for that
-        n = len(self._atomgroups[0])
 
         for chain in self._atomgroups:
             # Vector from each atom to next
@@ -266,8 +278,17 @@ def _single_frame(self):
             vecs /= np.sqrt((vecs * vecs).sum(axis=1))[:, None]
 
             inner_pr = np.inner(vecs, vecs)
-            for i in range(n - 1):
-                self._results[: (n - 1) - i] += inner_pr[i, i:]
+            for i in range(self.chainlength - 1):
+                self.results.raw_bond_autocorr[
+                    : (self.chainlength - 1) - i
+                ] += inner_pr[i, i:]
+
+    def _get_aggregator(self):
+        return ResultsGroup(
+            lookup={
+                "raw_bond_autocorr": ResultsGroup.ndarray_sum,
+            }
+        )
 
     @property
     def lb(self):
@@ -300,14 +321,12 @@ def fit(self):
         return self.results.fit
 
     def _conclude(self):
-        n = len(self._atomgroups[0])
-
-        norm = np.linspace(n - 1, 1, n - 1)
-        norm *= len(self._atomgroups) * self.n_frames
-
-        self.results.bond_autocorrelation = self._results / norm
+        norm = np.linspace(self.chainlength - 1, 1, self.chainlength - 1)
+        norm *= len(self._atomgroups) * self._trajectory.n_frames
+        self.results.bond_autocorrelation = (
+            self.results.raw_bond_autocorr / norm
+        )
         self._calc_bond_length()
-
         self._perform_fit()
 
     def _calc_bond_length(self):
@@ -350,7 +369,7 @@ def plot(self, ax=None):
         import matplotlib.pyplot as plt
 
         if ax is None:
-            fig, ax = plt.subplots()
+            _, ax = plt.subplots()
         ax.plot(
             self.results.x,
             self.results.bond_autocorrelation,

testsuite/MDAnalysisTests/analysis/conftest.py

@@ -18,6 +18,7 @@
 from MDAnalysis.analysis.contacts import Contacts
 from MDAnalysis.analysis.density import DensityAnalysis
 from MDAnalysis.analysis.lineardensity import LinearDensity
+from MDAnalysis.analysis.polymer import PersistenceLength
 from MDAnalysis.lib.util import is_installed
 
 
@@ -185,3 +186,11 @@ def client_DensityAnalysis(request):
 @pytest.fixture(scope="module", params=params_for_cls(LinearDensity))
 def client_LinearDensity(request):
     return request.param
+
+
+# MDAnalysis.analysis.polymer
+
+
+@pytest.fixture(scope="module", params=params_for_cls(PersistenceLength))
+def client_PersistenceLength(request):
+    return request.param

testsuite/MDAnalysisTests/analysis/test_persistencelength.py

@@ -36,24 +36,33 @@
 from MDAnalysisTests.datafiles import Plength, TRZ_psf, TRZ
 
 
+def test_class_is_parallelizable():
+    assert polymer.PersistenceLength._analysis_algorithm_is_parallelizable
+
+
+def test_supported_backends():
+    assert polymer.PersistenceLength.get_supported_backends() == (
+        "serial",
+        "multiprocessing",
+        "dask",
+    )
+
+
 class TestPersistenceLength(object):
     @staticmethod
     @pytest.fixture()
     def u():
         return mda.Universe(Plength)
 
-    @staticmethod
     @pytest.fixture()
-    def p(u):
+    def p(self, u):
         ags = [r.atoms.select_atoms("name C* N*") for r in u.residues]
-
         p = polymer.PersistenceLength(ags)
         return p
 
-    @staticmethod
     @pytest.fixture()
-    def p_run(p):
-        return p.run()
+    def p_run(self, p, client_PersistenceLength):
+        return p.run(**client_PersistenceLength)
 
     def test_ag_ValueError(self, u):
         ags = [u.atoms[:10], u.atoms[10:110]]
@@ -81,15 +90,11 @@ def test_raise_NoDataError(self, p):
     def test_plot_ax_return(self, p_run):
         """Ensure that a matplotlib axis object is
         returned when plot() is called."""
-        actual = p_run.plot()
-        expected = matplotlib.axes.Axes
-        assert isinstance(actual, expected)
+        assert isinstance(p_run.plot(), matplotlib.axes.Axes)
 
     def test_plot_with_ax(self, p_run):
         fig, ax = plt.subplots()
-
         ax2 = p_run.plot(ax=ax)
-
         assert ax2 is ax
 
     def test_current_axes(self, p_run):
@@ -98,8 +103,7 @@ def test_current_axes(self, p_run):
         assert ax2 is not ax
 
     @pytest.mark.parametrize("attr", ("lb", "lp", "fit"))
-    def test(self, p, attr):
-        p_run = p.run(step=3)
+    def test(self, p_run, attr):
         wmsg = f"The `{attr}` attribute was deprecated in MDAnalysis 2.0.0"
         with pytest.warns(DeprecationWarning, match=wmsg):
             getattr(p_run, attr) is p_run.results[attr]